scholarly journals Adaptive Computation Offloading for Mobile Augmented Reality

2021 ◽  
Vol 5 (4) ◽  
pp. 1-30
Author(s):  
Jie Ren ◽  
Ling Gao ◽  
Xiaoming Wang ◽  
Miao Ma ◽  
Guoyong Qiu ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Video Quality ◽  
Super Resolution ◽  
Computation Offloading ◽  
High Definition ◽  
High Quality ◽  
Adaptive Computation ◽  
Server Side ◽  
Video Feed ◽  
Mobile Ar

Augmented reality (AR) underpins many emerging mobile applications, but it increasingly requires more computation power for better machine understanding and user experience. While computation offloading promises a solution for high-quality and interactive mobile AR, existing methods work best for high-definition videos but cannot meet the real-time requirement for emerging 4K videos due to the long uploading latency. We introduce ACTOR, a novel computation-offloading framework for 4K mobile AR. To reduce the uploading latency, ACTOR dynamically and judiciously downscales the mobile video feed to be sent to the remote server. On the server-side, it leverages image super-resolution technology to scale back the received video so that high-quality object detection, tracking and rendering can be performed on the full 4K resolution. ACTOR employs machine learning to predict which of the downscaling resolutions and super-resolution configurations should be used, by taking into account the video content, server processing delay, and user expected latency. We evaluate ACTOR by applying it to over 2,000 4K video clips across two typical WiFi network settings. Extensive experimental results show that ACTOR consistently and significantly outperforms competitive methods for simultaneously meeting the latency and user-perceived video quality requirements.

High Definition Television (HDTV) and Video Surveillance

2014 ◽  
pp. 219-223
Keyword(s):  
Video Surveillance ◽  
Video Quality ◽  
Image Data ◽  
Good Choice ◽  
Frame Rate ◽  
Surveillance Video ◽  
High Definition ◽  
High Quality ◽  
High Definition Television ◽  
Quality Video

High definition television is becoming ever more popular, opening up the market to new high-definition technologies. Image quality and color fidelity have experienced improvements faster than ever. The video surveillance market has been affected by high definition television demand. Since video surveillance calls for large amounts of image data, high-quality video frame rates are generally compromised. However, a network camera that conforms to high definition television standards shows good performance in high frame rate, resolution, and color fidelity. High quality network cameras are a good choice for surveillance video quality.

scholarly journals Quality of Experience Assessment of Video Quality in Social Clouds

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Asif Ali Laghari ◽  
Hui He ◽  
Shahid Karim ◽  
Himat Ali Shah ◽  
Nabin Kumar Karn
Keyword(s):  
Video Compression ◽  
Quality Of Experience ◽  
Service Providers ◽  
Video Quality ◽  
Original Video ◽  
File Size ◽  
High Definition ◽  
High Quality ◽  
Video Sharing

Video sharing on social clouds is popular among the users around the world. High-Definition (HD) videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS). Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE) level of end users. To assess the QoE of video compression, we conducted subjective (QoE) experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

scholarly journals Flexible computation offloading in a fuzzy-based mobile edge orchestrator for IoT applications

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
VanDung Nguyen ◽  
Tran Trong Khanh ◽  
Tri D. T. Nguyen ◽  
Choong Seon Hong ◽  
Eui-Nam Huh
Keyword(s):  
Cloud Computing ◽  
Augmented Reality ◽  
Mobile Devices ◽  
Computing System ◽  
Mobile User ◽  
Computation Offloading ◽  
Context Aware ◽  
Computing Systems ◽  
Iot Applications ◽  
Service Times

AbstractIn the Internet of Things (IoT) era, the capacity-limited Internet and uncontrollable service delays for various new applications, such as video streaming analysis and augmented reality, are challenges. Cloud computing systems, also known as a solution that offloads energy-consuming computation of IoT applications to a cloud server, cannot meet the delay-sensitive and context-aware service requirements. To address this issue, an edge computing system provides timely and context-aware services by bringing the computations and storage closer to the user. The dynamic flow of requests that can be efficiently processed is a significant challenge for edge and cloud computing systems. To improve the performance of IoT systems, the mobile edge orchestrator (MEO), which is an application placement controller, was designed by integrating end mobile devices with edge and cloud computing systems. In this paper, we propose a flexible computation offloading method in a fuzzy-based MEO for IoT applications in order to improve the efficiency in computational resource management. Considering the network, computation resources, and task requirements, a fuzzy-based MEO allows edge workload orchestration actions to decide whether to offload a mobile user to local edge, neighboring edge, or cloud servers. Additionally, increasing packet sizes will affect the failed-task ratio when the number of mobile devices increases. To reduce failed tasks because of transmission collisions and to improve service times for time-critical tasks, we define a new input crisp value, and a new output decision for a fuzzy-based MEO. Using the EdgeCloudSim simulator, we evaluate our proposal with four benchmark algorithms in augmented reality, healthcare, compute-intensive, and infotainment applications. Simulation results show that our proposal provides better results in terms of WLAN delay, service times, the number of failed tasks, and VM utilization.

scholarly journals Rancang Bangun Modul Praktikum Teknik Digital Berbasis Mobile Augmented Reality (AR)

2014 ◽  
Vol 6 (2) ◽  
pp. 83 ◽  
Author(s):  
Elisa Usada
Keyword(s):  
Augmented Reality ◽  
Mobile Augmented Reality ◽  
Mobile Ar

Praktikum merupakan salah satu jenis pembelajaran yang dilaksanakan untuk mengasah keterampilan dan memperdalam pemahaman mahasiswa akan suatu materi, dengan menggunakan peralatan-peralatan praktek. Pelaksanaan praktikum mengacu pada petunjuk praktikum dan modul berisi materi yang akan dipraktekkan. Perkembangan teknologi media belajar memungkinkan modul praktikum untuk dikemas dalam bentuk yang lebih menarik, selain dalam bentuk buku teks konvensional. Media belajar berbasis AR (Augmented Reality) telah digunakan untuk mendukung aplikasi edukasi dalam berbagai domain, seperti sejarah, matematika, dan sebagainya. Penelitian ini bertujuan merancang dan membangun modul praktikum mata kuliah Teknik Digital berbasis mobile AR. Metodologi yang akan digunakan adalah melalui pendekatan prototype dengan langkah-langkah: mengumpulkan dan menganalisa kebutuhan; perancangan; membangun protototype. Hasil dari penelitian ini adalah sebuah prototype modul mata praktikum Teknik Digital berbasis mobile-AR. Prototype yang dihasilkan belum menampilkan model 3D yang lengkap. Sebagai langkah penelitian lanjutan, pembuatan model 3D yang lengkap akan dibuat dan prototype ini harus melalui proses evaluasi oleh konsumen, dilanjutkan dengan perubahan rancangan dan prototype apabila diperlukan, sebelum dibuat dalam skala besar dan diimplementasikan.

scholarly journals VISUALIZATION OF POINT CLOUD MODELS IN MOBILE AUGMENTED REALITY USING CONTINUOUS LEVEL OF DETAIL METHOD

2020 ◽  
Vol XLIV-4/W1-2020 ◽  
pp. 167-170
Author(s):  
L. Zhang ◽  
P. van Oosterom ◽  
H. Liu
Keyword(s):  
Augmented Reality ◽  
Point Cloud ◽  
Cloud Model ◽  
Point Clouds ◽  
Level Of Detail ◽  
Mobile Augmented Reality ◽  
Cloud Models ◽  
Point Cloud Model ◽  
Visual Artifacts ◽  
Mobile Ar

Abstract. Point clouds have become one of the most popular sources of data in geospatial fields due to their availability and flexibility. However, because of the large amount of data and the limited resources of mobile devices, the use of point clouds in mobile Augmented Reality applications is still quite limited. Many current mobile AR applications of point clouds lack fluent interactions with users. In our paper, a cLoD (continuous level-of-detail) method is introduced to filter the number of points to be rendered considerably, together with an adaptive point size rendering strategy, thus improve the rendering performance and remove visual artifacts of mobile AR point cloud applications. Our method uses a cLoD model that has an ideal distribution over LoDs, with which can remove unnecessary points without sudden changes in density as present in the commonly used discrete level-of-detail approaches. Besides, camera position, orientation and distance from the camera to point cloud model is taken into consideration as well. With our method, good interactive visualization of point clouds can be realized in the mobile AR environment, with both nice visual quality and proper resource consumption.

scholarly journals Structuring Augmented Reality Information on the stemua.science

2018 ◽  
Vol 51 ◽  
pp. 102-114
Author(s):  
Віктор Шаповалов ◽  
Артем Атамась ◽  
Жанна Білик ◽  
Євгеній Шаповалов ◽  
Олександр Учитель
Keyword(s):  
Augmented Reality ◽  
High Quality ◽  
Closed Type

Shapovalov V.V., Atamas A.I., Bilyk Zh.I., Shapovalov YE.V. and Uchytel A.D. Structuring Augmented Reality Information on the stemua.science. It is demonstrated that one of the conditions for successful scientific and pedagogical work is exchanging of methodical materials, including with using of augmented reality. We propose to classify approaches of placing methodical materials on closed, open and open-moderated types. One of the important benefits of a closed type is the high quality of the methodical material, but it’s limited by amount of material and the lack of exchange opportunities that are problems, and there are no open-moderated resources in the Ukrainian language. The aim of this article is to analyze approaches of systematization of methodical material with using of augmented reality and recommend using of STEMUA for systematization of them. It is shown that STEMUA allows teachers to develop methodical material and place it on this platform. The platform automatically organizes methodical material in the database. Consequently, the platform is satisfying the methodical needs of Ukrainian teachers for material with using of complementary reality in the teaching. It is recommended for teachers and methodists to provide development and methodical materials with using of augmented reality and add them to the platform database.  

Towards the Integration of Mobile Augmented Reality within an Aluminium Process Fault Detection and Diagnosis System

2013 ◽  
Vol 845 ◽  
pp. 703-707 ◽  
Author(s):  
Abd Majid Nazatul Aini ◽  
Haslina Arshad
Keyword(s):  
Augmented Reality ◽  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Industrial Plant ◽  
Mobile Augmented Reality ◽  
Design Quality ◽  
Diagnosis System ◽  
Aluminium Smelting ◽  
Detection And Diagnosis ◽  
Mobile Ar

Mobile Augmented Reality (AR), which mixes the real world and the virtual world on hand-held devices, is a growing area of the manufacturing industry. Since mobile AR can be used to augment a users view of an industry plant, it provides alternative solutions for design, quality control, monitoring and control, service, and maintenance in complex process industries, such as the aluminium smelting industry. The objective of this paper is to discuss the integration of mobile AR within an aluminium industrial plant, in order to achieve effective fault detection and diagnosis. The possible integration of mobile AR within an aluminium fault detection and diagnosis system is shown with regard to four main functions, namely (1) plant information system, (2) fault history, (3) interactive troubleshooting, and (4) statistical analysis results. This paper opens up possible future works, where the potential use of mobile AR can be explored as an additional user interface component, for increasing the effectiveness of process monitoring within the aluminium smelting process.

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